Skip to main content
Book cover

Urban Social Listening pp 27–33Cite as

Palgrave Macmillan

Taking Microblogging Data for a Test Drive

  • 437 Accesses

Abstract

In this chapter we provide an account of our attempt to analyze Twitter data. We describe our methods for creating a database of over 100,000 tweets produced by users in the city of New Bedford, Massachusetts. We attempt to analyze the way in which the Twitter messages engaged with the topics of urban policy and find there is a cursory overlap. We also compare the commercially available IBM SPSS Modeler to our custom-designed sentiment analyzer. Both methods showed a relatively low percentage of sentiment overall but a greater prevalence of positive tweets. Overall, we note that the magnitude of microblogging data and the ability to capture it readily and improvements in analysis techniques may allow for quantity to compensate for low percentages of sentiment.

Keywords

  • New Bedford
  • Twitter
  • Sentiment analysis

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1057/978-1-137-59491-4_3
  • Chapter length: 7 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   54.99
Price excludes VAT (USA)
  • ISBN: 978-1-137-59491-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   69.99
Price excludes VAT (USA)
Hardcover Book
USD   69.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 3.1

References

  • Gaber, J., & Gaber, S. (2007). Qualitative analysis for planning & policy: Beyond the numbers. Chicago: APA Planners Press.

    Google Scholar 

  • Hansen, L. K., Arvidsson, A., Nielsen, F. Å., Colleoni, E., & Etter, M. (2011). Good friends, bad news—Affect and virality in Twitter. The 2011 International Workshop on Social Computing, Network, and Services (SocialComNet).

    Google Scholar 

  • Ngoc, P. T., & Yoo, M. (2014). The lexicon-based sentiment analysis for fan page ranking in Facebook. In Information Networking (ICOIN), 2014 International Conference on, IEEE, 444–448.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Tufts University, Medford, Massachusetts, USA

    Justin B. Hollander, Cara Foster-Karim, Andrew Wiley & Dibyendu Das

  2. Urban Planner and Sociologist, Cambridge, USA

    Erin Graves

  3. University of Massachusetts Amherst, Amherst, Massachusetts, USA

    Henry Renski

Authors
  1. Justin B. Hollander
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Erin Graves
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Henry Renski
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cara Foster-Karim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andrew Wiley
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dibyendu Das
    View author publications

    You can also search for this author in PubMed Google Scholar

Copyright information

© 2016 The Author(s)

About this chapter

Cite this chapter

Hollander, J.B., Graves, E., Renski, H., Foster-Karim, C., Wiley, A., Das, D. (2016). Taking Microblogging Data for a Test Drive. In: Urban Social Listening. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-59491-4_3

Download citation